Visual embedding models excel at zero-shot tasks like visual retrieval and classification. However, these models cannot be used for tasks that contain ambiguity or require user instruction. These tasks necessitate a multimodal embedding model, which outputs embeddings that combine visual and natural language input. Existing CLIP-based approaches embed images and text independently, and fuse the result. We find that this results in weak interactions between modalities, and poor user control over the representation. We introduce ABC, an open-source multimodal embedding model that uses a vision-language model backbone to deeply integrate image features with natural language instructions. ABC achieves bestfor-size performance on MSCOCO image-to-text retrieval and is the top performing model on classification and VQA tasks in the Massive Multimodal Embedding Benchmark. With a strongly unified vision-language representation, ABC can use natural language to solve subtle and potentially ambiguous visual retrieval problems. To evaluate this capability, we design CtrlBench, a benchmark that requires interleaving textual instructions with image content for correct retrieval. ABC advances the state of multimodal embeddings by offering high-quality representations and flexible natural language control. Our model and datasets are available at our project page.

The authors argue that accelerating/decelerating return constraints can help model interpretability. To this end, they propose two methods: (i) an extension of input convex neural networks that supports monotonicity constraints; (ii) an extension of partial monotonic lattice models that supports concavity/convexity constraints. The proposed methods are compared to several constrained and unconstrained baselines on different datasets. Pros: - The paper is very well written, and definitely relevant to NIPS - Constraining the model to have accelerating returns w.r.t. It seems that the term "interpretability" here is used as a synonym of "visualizability".

Approaching artificial intelligence for your business activities is considered to be an agile opinion towards managing your business. Artificial Intelligence is one of the rising element in business as well as the general world. Artificial Intelligence is a very broad concept focusing on automating the operation that helps in reducing human effort, maintaining efficiency & effectiveness and enhance the working criteria. AI technologies offer a scalable way to cope with the heavy amount of data in a managed way to utilize it in an effective manner. AI avails the creation of an advanced workplace that greatens on seamless collaboration between the enterprise system and individual.

AWS has unveiled a host of enhancements for Amazon SageMaker, its end-to-end machine learning offering.

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner How to grow skills as an AI Engineer / Researcher? In 10 years of working as an AI researcher, here are three lessons I've learnt along the way: ❶ Learn more about data pipeline to have better control of your data. Most of the time, AI researchers solve well-defined problems with well-curated datasets. This tends to form an illusion that the model is solving everything and you may overlook the data lineage and the data governance issues. Don't get too comfortable about the well-curated datasets in the lab!

Joe Toscano is an award-winning designer and former consultant for Google who left in 2017 due to ethical concerns. Upgrade your inbox and get our editors' picks twice a month. Privacy is a fundamental human right that has become one of the most illusive and least understood topics of the Internet. However, the time is coming for change, and it's up to us whether that's going to happen willfully or through regulation. This article will explain exactly why making these changes is so critical to the success of your business and how you can make the changes that need to be made in a way that also positively impacts your bottom line. Privacy is a fundamental human right that allows us to be our true selves. It's what allows us to be weirdos without shame. It allows us to have dissenting opinions without consequence.